wehub-resource-sync
389 lines
14 KiB
C++
389 lines
14 KiB
C++
/*
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* SPDX-FileCopyrightText: Copyright (c) 1993-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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* SPDX-License-Identifier: Apache-2.0
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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// Docstrings for the pyOnnx parser bindings.
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#pragma once
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namespace tensorrt
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{
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namespace OnnxParserDoc
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{
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constexpr char const* descr = R"trtdoc(
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This class is used for parsing ONNX models into a TensorRT network definition
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:ivar num_errors: :class:`int` The number of errors that occurred during prior calls to :func:`parse`
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)trtdoc";
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constexpr char const* init = R"trtdoc(
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:arg network: The network definition to which the parser will write.
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:arg logger: The logger to use.
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)trtdoc";
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constexpr char const* parse = R"trtdoc(
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Parse a serialized ONNX model into the TensorRT network.
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:arg model: The serialized ONNX model.
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:arg path: The path to the model file. Only required if the model has externally stored weights.
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:returns: true if the model was parsed successfully
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)trtdoc";
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constexpr char const* parse_from_file = R"trtdoc(
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Parse an ONNX model from file into a TensorRT network.
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:arg model: The path to an ONNX model.
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:returns: true if the model was parsed successfully
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)trtdoc";
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constexpr char const* supports_model_v2 = R"trtdoc(
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Check whether TensorRT supports a particular ONNX model.
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Query each subgraph with num_subgraphs, is_subgraph_supported, get_subgraph_nodes.
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:arg model: The serialized ONNX model.
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:arg path: The path to the model file. Only required if the model has externally stored weights.
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:returns: true if the model is supported
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)trtdoc";
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constexpr char const* num_subgraphs = R"trtdoc(
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Get the number of subgraphs. Calling before \p supportsModelV2 is an undefined behavior. Will return 0 by default.
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:returns: Number of subgraphs
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)trtdoc";
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constexpr char const* is_subgraph_supported = R"trtdoc(
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Returns whether the subgraph is supported. Calling before \p supportsModelV2 is an undefined behavior.
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Will return false by default.
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:arg index: Index of the subgraph to be checked.
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:returns: true if subgraph is supported
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)trtdoc";
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constexpr char const* get_subgraph_nodes = R"trtdoc(
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Get the nodes of the specified subgraph. Calling before \p supportsModelV2 is an undefined behavior.
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Will return an empty list by default.
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:arg index: Index of the subgraph.
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:returns: List[int]
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A list of node indices in the subgraph.
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)trtdoc";
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constexpr char const* supports_operator = R"trtdoc(
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Returns whether the specified operator may be supported by the parser.
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Note that a result of true does not guarantee that the operator will be supported in all cases (i.e., this function may return false-positives).
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:arg op_name: The name of the ONNX operator to check for support
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)trtdoc";
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constexpr char const* get_error = R"trtdoc(
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Get an error that occurred during prior calls to :func:`parse`
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:arg index: Index of the error
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)trtdoc";
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constexpr char const* clear_errors = R"trtdoc(
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Clear errors from prior calls to :func:`parse`
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)trtdoc";
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constexpr char const* clear_flag = R"trtdoc(
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Clears the parser flag from the enabled flags.
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:arg flag: The flag to clear.
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)trtdoc";
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constexpr char const* get_flag = R"trtdoc(
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Check if a build mode flag is set.
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:arg flag: The flag to check.
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:returns: A `bool` indicating whether the flag is set.
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)trtdoc";
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constexpr char const* set_flag = R"trtdoc(
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Add the input parser flag to the already enabled flags.
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:arg flag: The flag to set.
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)trtdoc";
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constexpr char const* get_layer_output_tensor = R"trtdoc(
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Get the i-th output ITensor object for the ONNX layer "name".
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In the case of multiple nodes sharing the same name this function will return
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the output tensors of the first instance of the node in the ONNX graph.
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:arg name: The name of the ONNX layer.
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:arg i: The index of the output.
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:returns: The output tensor or None if the layer was not found or an invalid index was provided.
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)trtdoc";
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constexpr char const* get_used_vc_plugin_libraries = R"trtdoc(
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Query the plugin libraries needed to implement operations used by the parser in a version-compatible engine.
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This provides a list of plugin libraries on the filesystem needed to implement operations
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in the parsed network. If you are building a version-compatible engine using this network,
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provide this list to IBuilderConfig.set_plugins_to_serialize() to serialize these plugins along
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with the version-compatible engine, or, if you want to ship these plugin libraries externally
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to the engine, ensure that IPluginRegistry.load_library() is used to load these libraries in the
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appropriate runtime before deserializing the corresponding engine.
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:returns: List[str] List of plugin libraries found by the parser.
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:raises: :class:`RuntimeError` if an internal error occurred when trying to fetch the list of plugin libraries.
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)trtdoc";
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constexpr char const* load_model_proto = R"trtdoc(
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Load a serialized ONNX model into the parser. Unlike the parse() or parse_from_file()
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functions, this function does not immediately convert the model into a TensorRT INetworkDefinition. Using this function
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allows users to provide their own initializers for the ONNX model through the load_initializer() function.
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Only one model can be loaded at a time. Subsequent calls to load_model_proto() will result in an error.
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To begin the conversion of the model into a TensorRT INetworkDefinition, use parse_model_proto().
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:arg model: The serialized ONNX model.
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:arg path: The path to the model file. Only required if the model has externally stored weights.
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:returns: true if the model was loaded successfully
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)trtdoc";
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constexpr char const* load_initializer = R"trtdoc(
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Prompt the ONNX parser to load an initializer with user-provided binary data.
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The lifetime of the data must exceed the lifetime of the parser.
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All user-provided initializers must be provided prior to calling parse_model_proto().
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This function can be called multiple times to specify the names of multiple initializers.
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Calling this function with an initializer previously specified will overwrite the previous instance.
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This function will return false if initializer validation fails. Possible validation errors are:
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* This function was called prior to load_model_proto().
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* The requested initializer was not found in the model.
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* The size of the data provided is different from the corresponding initializer in the model.
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:arg name: name of the initializer.
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:arg data: binary data of the initializer.
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:arg size: the size of the binary data.
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:returns: true if the initializer was successfully loaded
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)trtdoc";
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constexpr char const* parse_model_proto = R"trtdoc(
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Begin the parsing and conversion process of the loaded ONNX model into a TensorRT INetworkDefinition.
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:returns: true if the model was parsed successfully.
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)trtdoc";
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constexpr char const* set_builder_config = R"trtdoc(
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Set the BuilderConfig for the parser.
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:arg builder_config: The BuilderConfig to set.
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:returns: true if the BuilderConfig was set successfully, false otherwise.
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)trtdoc";
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} // namespace OnnxParserDoc
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namespace OnnxParserRefitterDoc
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{
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constexpr char const* descr = R"trtdoc(
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This is an interface designed to refit weights from an ONNX model.
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)trtdoc";
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constexpr char const* init = R"trtdoc(
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:arg refitter: The Refitter object used to refit the model.
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:arg logger: The logger to use.
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)trtdoc";
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constexpr char const* refit_from_bytes = R"trtdoc(
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Load a serialized ONNX model from memory and perform weight refit.
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:arg model: The serialized ONNX model.
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:arg path: The path to the model file. Only required if the model has externally stored weights.
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:returns: true if all the weights in the engine were refit successfully.
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)trtdoc";
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constexpr char const* refit_from_file = R"trtdoc(
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Load and parse a ONNX model from disk and perform weight refit.
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:arg model: The path to an ONNX model.
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:returns: true if the model was loaded successfully, and if all the weights in the engine were refit successfully.
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)trtdoc";
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constexpr char const* get_error = R"trtdoc(
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Get an error that occurred during prior calls to :func:`refitFromBytes` or :func:`refitFromFile`.
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:arg index: Index of the error
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)trtdoc";
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constexpr char const* clear_errors = R"trtdoc(
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Clear errors from prior calls to :func:`refitFromBytes` or :func:`refitFromFile`.
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)trtdoc";
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constexpr char const* load_model_proto = R"trtdoc(
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Load a serialized ONNX model into the refitter. Unlike the refit() or refit_from_file()
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functions, this function does not immediately begin the refit process. Using this function
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allows users to provide their own initializers for the ONNX model through the load_initializer() function.
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Only one model can be loaded at a time. Subsequent calls to load_model_proto() will result in an error.
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To begin the refit process, use refit_model_proto().
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:arg model: The serialized ONNX model.
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:arg path: The path to the model file. Only required if the model has externally stored weights.
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:returns: true if the model was loaded successfully.
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)trtdoc";
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constexpr char const* load_initializer = R"trtdoc(
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Prompt the ONNX refitter to load an initializer with user-provided binary data.
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The lifetime of the data must exceed the lifetime of the refitter.
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All user-provided initializers must be provided prior to calling refit_model_proto().
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This function can be called multiple times to specify the names of multiple initializers.
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Calling this function with an initializer previously specified will overwrite the previous instance.
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This function will return false if initializer validation fails. Possible validation errors are:
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* This function was called prior to load_model_proto().
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* The requested initializer was not found in the model.
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* The size of the data provided is different from the corresponding initializer in the model.
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:arg name: name of the initializer.
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:arg data: binary data of the initializer.
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:arg size: the size of the binary data.
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:returns: true if the initializer was successfully loaded.
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)trtdoc";
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constexpr char const* refit_model_proto = R"trtdoc(
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Begin the refit process from the loaded ONNX model.
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:returns: true if the model was refit successfully.
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)trtdoc";
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} // namespace OnnxParserRefitterDoc
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namespace ErrorCodeDoc
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{
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constexpr char const* descr = R"trtdoc(
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The type of parser error
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)trtdoc";
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} // namespace ErrorCodeDoc
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namespace OnnxParserFlagDoc
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{
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constexpr char const* descr = R"trtdoc(
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Flags that control how an ONNX model gets parsed.
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)trtdoc";
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constexpr char const* NATIVE_INSTANCENORM = R"trtdoc(
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Parse the ONNX model into the INetworkDefinition with the intention of using TensorRT's native layer implementation over the plugin implementation for InstanceNormalization nodes.
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This flag is required when building version-compatible or hardware-compatible engines.
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This flag is ON by default.
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)trtdoc";
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constexpr char const* ENABLE_UINT8_AND_ASYMMETRIC_QUANTIZATION_DLA = R"trtdoc(
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Enable UINT8 as a quantization data type and asymmetric quantization with non-zero zero-point values in Quantize and Dequantize nodes.
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The resulting engine must be built targeting DLA version >= 3.16.
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This flag is OFF by default.
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)trtdoc";
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constexpr char const* REPORT_CAPABILITY_DLA = R"trtdoc(
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Parse the ONNX model with per-node validation for DLA. If this flag is set, is_subgraph_supported() will
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also return capability in the context of DLA support.
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When this flag is set, a valid BuilderConfig must be provided to the parser via set_builder_config().
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This flag is OFF by default.
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)trtdoc";
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constexpr char const* ENABLE_PLUGIN_OVERRIDE = R"trtdoc(
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Allow a loaded plugin with the same name as an ONNX operator type to override the default ONNX implementation,
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even if the plugin namespace attribute is not set.
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This flag is useful for custom plugins that are intended to replace standard ONNX operators, for example to provide
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alternative implementations or improved performance.
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This flag is OFF by default.
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)trtdoc";
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constexpr char const* ADJUST_FOR_DLA = R"trtdoc(
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Parse the ONNX model with adjustments to make layers more amenable to running on DLA.
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This flag is OFF by default.
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)trtdoc";
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} // namespace OnnxParserFlagDoc
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namespace ParserErrorDoc
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{
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constexpr char const* descr = R"trtdoc(
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An object containing information about an error
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)trtdoc";
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constexpr char const* code = R"trtdoc(
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:returns: The error code
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)trtdoc";
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constexpr char const* desc = R"trtdoc(
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:returns: Description of the error
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)trtdoc";
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constexpr char const* file = R"trtdoc(
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:returns: Source file in which the error occurred
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)trtdoc";
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constexpr char const* line = R"trtdoc(
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:returns: Source line at which the error occurred
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)trtdoc";
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constexpr char const* func = R"trtdoc(
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:returns: Source function in which the error occurred
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)trtdoc";
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constexpr char const* node = R"trtdoc(
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:returns: Index of the Onnx model node in which the error occurred
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)trtdoc";
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constexpr char const* node_name = R"trtdoc(
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:returns: Name of the node in the model in which the error occurred
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)trtdoc";
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constexpr char const* node_operator = R"trtdoc(
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:returns: Name of the node operation in the model in which the error occurred
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)trtdoc";
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constexpr char const* local_function_stack = R"trtdoc(
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:returns: Current stack trace of local functions in which the error occurred
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)trtdoc";
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constexpr char const* local_function_stack_size = R"trtdoc(
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:returns: Size of the current stack trace of local functions in which the error occurred
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)trtdoc";
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} // namespace ParserErrorDoc
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constexpr char const* get_nv_onnx_parser_version = R"trtdoc(
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:returns: The Onnx Parser version
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)trtdoc";
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} // namespace tensorrt
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